'''
Created on 2013-3-10

@author: marlon
'''
import numpy as np
from Recurrent import Recurrent
from Network import Network
from ConstantObj import ConstantObj

print "hello world"
inputData = np.array([[1, 2, 3, 4],[4, 5, 6, 7]])
recurrent = Recurrent();
network = Network();

recurrent.perceptionLearning(inputData,network)

'''
twoArray1 = ([1,2],[5,3],[7,4],[5,3])
print twoArray1.count([5,3])

oneArray = (2,3)

oneArray2 = np.array(oneArray)
oneArray3 = oneArray2.reshape((-1,1))

oneArray4 = np.matrix(oneArray)

twoArray2 = np.matrix(twoArray1)

print oneArray4.transpose()

print twoArray2.shape
print"--------"

thirdArray =  twoArray2 * oneArray4.transpose()

print thirdArray

'''
'''
print"--------"
twoArray = np.array([[[1, 2, 3, 4],[4, 5, 6, 7], [7, 8, 9, 10]],[[-1, -2, -3, -4],[-4, -5, -6, -7], [-7, -8, -9, -10]]])
print twoArray.shape

for i in range(twoArray.shape[0]):
    print i
    print twoArray[i]
    
'''